A

absorbNodes()node: absorbingabsorbing nodeslink: automatically addedremove nodesumming out a variablemaxing out a variableAbsorbs the passed nodes, so that they are removed from the net, but the net's overall joint probability distribution for the remaining nodes is unchanged.

addCases()degree of casesCaseset: in usefindings: getting from databasecase: getting from databaseDatabaseManager: making case-setCaseset: getting from databasedatabase: getting cases fromSELECT SQL commandSQL commands: SELECTaddCases: in useDatabaseManager: in useCaseset: in useDatabaseManager: in useLearner: in useLearner: in use EM_LEARNING: in uselearnCPTs: in useSearches the database attached to dbMgr for cases to add to this caseset.

addNodes()getAllNodesetsnode-set: retrieving allnode-set: ordering by prioritypriority order of node-setsorder of node-sets- in node-set namesdash in node-set namescase file: readingfavor_discrete, for nodes from DBfavor_continuous, for nodes from DB

B

C

calcState()UNDEF_STATEnode: inferencedeterministic updatingequation: evaluatingReturns the discrete finding entered for this node if one has been entered, or the state calculated from its neighbors if that can be done deterministically (e.g., by equation or function table), or else UNDEF_STATE.

calcValue() UNDEF_DBLnode: inferencedeterministic updatingequation: evaluatingReturns the real-valued finding entered for this node if one has been entered, or the real value calculated from its neighbors if that can be done deterministically (e.g., by equation or function table), or else UNDEF_DBL.

createCustomReport()Creates a text (possibly HTML, RTF, TXT, etc.) report on this net, which is completely customizable using a text template, and can include a wide variety of information on the net, its nodes, links, probability tables, current findings, beliefs, decisions, sensitivity, junction tree, etc.

enterGaussian()finding: entering GaussianGaussian findingnormal distribution findingEnters a likelihood finding for this Value object equivalent to a Gaussian distribution (normal distribution) with a mean of mean and a standard deviation of stddev.

equationToTable()node: equationcompile net: preparing fortables: building from equationequation: building tablegenerating table from equationBuilds the CPT for this node based on the equation that has been associated with it (see setEquation).

F

fadeCPTable()tables: fadingCPT table: fadingSmoothes the conditional probabilities (CPT) of this node to indicate greater uncertainty, which accounts for the idea that the world may have changed a little since they were last learned.

getBeliefs()probability (as float)node: inferencebelief updatingpropagating beliefsbeliefs: calculatingposterior probabilities: calculating
Returns a belief vector indicating the current probability for each state of this node.

getComment()node: commentcomment: for node, net, or statenet: commentcomment: for netstate: commentcomment: for statedescriptive text for net, node, or stateGets the documentation text concerning this object.

getConfusion()predicted vs actualNetTester: confusion matrixconfusion matrixReturns the number of times the Net predicted predictedState for node, but the case file actually held actualState as the value of that node, during the performance test of a net.

getCPTable()probability (as float)node: CPT tabletables: retrievingtables: conditional probabilityCPT table: retrievingReturns the conditional probabilities of this node, given that its parents are in the states indicated by the parentStates vector, by looking them up in the node's CPT table.

getElimOrder()net: elimination orderelimination orderReturns a list of the nodes of this net in their "elimination order" (which is used for triangulation in the compilation of this net), or null if there is no order currently associated with this net.

getExpectedValue()standard deviation UNDEF_DBLnode: inferenceexpected valueReturns the expected real value of this node, based on the current beliefs for this node, and if moments is non-null, moments will be filled with the moments as well.

getExperTable() UNDEF_DBLnode: experience tabletables: retrievingtables: experienceexperience table: retrievingnumber of casesestimated sample sizeessGiven parentStates, a vector of states for the parents of this node, this returns the "experience" of the node for the situation described by the parent states.

getFindingsProbability()net: probability of findingsjoint probability of findingsprobability of all findingscase: probability offindings: probability ofReturns the joint probability of the findings entered into net so far (including any negative or likelihood findings).

getLevels()level of discretized node (as double)node: levelsstates: levelsReturns the list of numbers used to enable a continuous node to act discrete, or enables a discrete node to provide real-valued numbers.

getMutualInfo()self informationSensitivity: for mutual infoSensitivity: for entropymutual informationentropymutual informationentropy reductionMeasures the mutual information between two nodes, which is how much a finding at one node (called the "varying node") is expected to alter the beliefs (measured as decrease in its entropy) at another node (called the "query node").

getPosition()coordinates of nodelocation of nodecenter of nodenode: visual positionvisual appearance: position of nodeposition of nodeRetrieves as elements 0 and 1 respectively, the x,y coordinates of the center of this node, as it would appear in a visual display (e.g., in Netica Application).

getReal()finding: retrievingpositive finding, real-valued: retrievingreal-valued finding: retrievingReturns the real-valued finding entered for this node, or UNDEF_DBL if none has been entered since the last retraction (call to clear).

getVarianceOfReal()expected value: sensitivityexpected decrease in variancevariance of a nodeSensitivity: for variancevariance reductionMeasures how much a finding at one node (called the "varying node") is expected to reduce the variance of another node (called the "query node").

getVersionString()Returns a String consisting of the full version number, a space, a code for the type of machine or OS it is running on, a comma, the name of the program, and finally a code indicating some build information (in parentheses).

insertFindings()findings: putting in databasecase: putting in databaseDatabaseManager: filling DBdatabase: populating from findingsINSERT SQL commandSQL commands: INSERTDatabaseManager: in useDatabaseManager: in useinsertFindings: in useenterFindingNot: in useCreates a new record in the database dbMgr consisting of the current findings.

isDeterministic()CPT table: test if deterministicnode: tablestables: test if deterministicfunction table: testdeterministic testWhether the value of this node, given its parents, is deterministic (versus probabilistic).

A class that holds information on errors that occurred while Netica was attempting some operation (which become part of the NeticaException thrown), or on warnings or other status reports of successful Netica operations.

NetTester()grading a Bayes netprediction: testingdiagnosis: testingNetTester: creatingnet: testing performanceperformance testingtesting performance of netNetTester: in usetestWithCaseset: in usePrintConfusionMatrix: in usegetConfusion: in usegetErrorRate: in usegetLogLoss: in usefinalize: in useCreates a NetTester which is a tool for grading a Bayes net, using a set of real cases to see how well the predictions or diagnosis of the net match the actual cases.

readFindings()text file as databasefindings: reading from fileCaseset position (as long)Streamer: reading findings fromcase file: reading FIRST_CASE NEXT_CASE NO_MORE_CASESReads a set of findings (i.e., a case) from a file containing one or more cases.

reorderNodesets()node-set: ordering by prioritypriority order of node-setsorder of node-setscolor of nodevisual appearance: color of nodeThis rearranges the priority order of the node-sets of this net.

retractFindings()net: retracting all findingsfindings: retractingfinding: retractingRetracts all findings (i.e., the current case) from all the nodes in this net, except "constant" nodes (use Node.finding().clear() for that).

reviseCPTsByCaseFile()degree of casestext file as databasecase file: learning CPTs fromnode: CPT tabletables: learningCPT table: learninglearning from dataRevises the CPTs of these nodes, to account for the cases in the given file.

reviseCPTsByFindings()degree of casesfindings: learning fromnode: CPT tabletables: learningCPT table: learninglearning from dataRevises the CPTs of these nodes, to account for the currently entered case.

Sensitivity()query nodevarying nodetarget nodeutility-free value of information ENTROPY_SENSV REAL_SENSV VARIANCE_SENSVSensitivity: creatingsensitivity to findingsSensitivity: in useSensitivity: in use ENTROPY_SENSV: in usefinalize: in usesensitivity to findingsvalue of informationmutual informationentropy reductionvariance reductionCreates a sensitivity measuring object, which measures how much the beliefs at one node (called the "query node" or "target node") will change if a finding is entered at another node (called the "varying node").

setMaxIterations()maximum iterations during learningiterations, controling learningtermination of learning algorithmLearner: termination conditionSets the maximum number of learning-step iterations (i.e., complete passes through the data) which will be done when learner is used, after which learning will be automatically terminated.

setMaxTolerance()maximum tolerance during learningtolerance, controling learningtermination of learning algorithmLearner: termination conditionSets the tolerance for the minimum change in data log likelihood between consecutive passes through the data, as a termination condition for any learning to be done by learner.

setMissingDataChar()case file: missing data char* in case file? in case filemissing data characterEnviron: setting case file charsSets the symbol to be used for indicating missing data fields in a case file created by Netica.

setPassword().neta file format: in useStreamer: setting passwordStreamer: in useencryptionencryptionpassword for encryptionSets the password that Netica will use for either encrypting an output stream, or for decrypting an input stream.

setPosition()coordinates of nodelocation of nodecenter of nodemove node on diagramnode: visual positionvisual appearance: position of nodeposition of nodeMoves this node so that its center is at coordinates (x, y), for any visual display (e.g., in Netica Application).

setRandomGenerator()Associates a random generator randomGenerator with this net, so that all operations on this net that require randomness will use randomGenerator (unless overridden by another generator, as described in documentation for the particular function being used).

setStateFuncTable() WILDCARD_STATEnode: function tabletables: settingfunction table: setting EVERY_STATESets the state value of this (discrete or discretized) deterministic node as a function of its parent nodes.

sizeCompiled()junction tree: sizenet: size compiledmemory requiredspeed of inferencecompile net: size resultingsize of junction treespeed of inferenceReturns the total size of the internal structure created by compiling a net (i.e., the junction tree, including sepsets), considering the findings currently entered.

T

testWithCaseset()NumCases column in case fileNetTester: doing testsScans through the case data in caseset to do a number of performance tests on a Bayes net (specified when creating the this NetTester).

undoLastOperation()node: undoing changenet: undoing changereversing net operationerror recovery: reversing operationsatomic operations: undoingUndoes the last operation done to this net (or any node in it), leaving the net in the same state as it was before the operation was done.

writeFindings()findings: writing to filenet: writing findings to fileStreamer: writing toCaseset position (as long)case file: creatingSaves in file the set of findings currently entered in nodeList, so that later they can be read back with readFindings.